A cool thing about LLM is they have infinite patience. They can go back and forth with the user until they either sort out how to make a useable bug report, or give up.
The only relationship you can have between these is that a ticket with a "resolved" status can be used as a KPI, but you're trying to invert the relationship here, which doesn't work. After all, it's an indicator and not a causal relationship
"average time to resolution" is also susceptible.
Both of these are pretty common all over the place, including OSS e.g. https://isitmaintained.com/#metrics
I suspect this sort of thing is one of the major motivations for the (as a user/reporter) infuriating rise in automated "this bug hasn't been touched in NN days, autoclosing for staleness" bots on various issue trackers.
I’m not sure what to think about the auto-close bots. Which do you think would be more annoying as the person who made the report: having a report that just sits there forever and you just have to hope somebody decided to pick it up, or having the issue auto-closed? (I’m truly and honestly not sure). At least in the case of the former you have a clear marker for when you should try again. But getting rejected by a bot can definitely be annoying.
I’m not sure how it would work out in the case of a free, community driven project, though. The goal isn’t to serve users, it is to convert users into helpful community members. If the bot converts people who wouldn’t otherwise be converted, it seems like a win. If it chases away users who could have been converted with human intervention, that’s a lose. But the human community members can always jump into the thread as well… if the bot is filtering out lots of people and nobody from the community is intervening, I guess that tells us something about the priorities of the community, haha.